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Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications

The rapid development of modern science nowadays makes it rather challenging to pick out valuable ideas from massive scientific literature. Existing widely-adopted citation-based metrics are not adequate for measuring how well the idea presented by a single publication is developed and whether it is...

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Autores principales: Li, Qi, Wang, Xinbing, Fu, Luoyi, Wang, Jianghao, Yao, Ling, Gan, Xiaoying, Zhou, Chenghu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518912/
https://www.ncbi.nlm.nih.gov/pubmed/36170296
http://dx.doi.org/10.1371/journal.pone.0275192
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author Li, Qi
Wang, Xinbing
Fu, Luoyi
Wang, Jianghao
Yao, Ling
Gan, Xiaoying
Zhou, Chenghu
author_facet Li, Qi
Wang, Xinbing
Fu, Luoyi
Wang, Jianghao
Yao, Ling
Gan, Xiaoying
Zhou, Chenghu
author_sort Li, Qi
collection PubMed
description The rapid development of modern science nowadays makes it rather challenging to pick out valuable ideas from massive scientific literature. Existing widely-adopted citation-based metrics are not adequate for measuring how well the idea presented by a single publication is developed and whether it is worth following. Here, inspired by traditional X-ray imaging, which returns internal structure imaging of real objects along with corresponding structure analysis, we propose Scientific X-ray, a framework that quantifies the development degree and development potential for any scientific idea through an assembly of ‘X-ray’ scanning, visualization and parsing operated on the citation network associated with a target publication. We pick all 71,431 scientific articles of citation counts over 1,000 as high-impact target publications among totally 204,664,199 publications that cover 16 disciplines spanning from 1800 to 2021. Our proposed Scientific X-ray reproduces how an idea evolves from the very original target publication all the way to the up to date status via an extracted ‘idea tree’ that attempts to preserve the most representative idea flow structure underneath each citation network. Interestingly, we observe that while the citation counts of publications may increase unlimitedly, the maximum valid idea inheritance of those target publications, i.e., the valid depth of the idea tree, cannot exceed a limit of six hops, and the idea evolution structure of any arbitrary publication unexceptionally falls into six fixed patterns. Combined with a development potential index that we further design based on the extracted idea tree, Scientific X-ray can vividly tell how further a given idea presented by a given publication can still go from any well-established starting point. Scientific X-ray successfully identifies 40 out of 49 topics of Nobel prize as high-potential topics by their prize-winning papers in an average of nine years before the prizes are released. Various trials on articles of diverse topics also confirm the power of Scientific X-ray in digging out influential/promising ideas. Scientific X-ray is user-friendly to researchers with any level of expertise, thus providing important basis for grasping research trends, helping scientific policy-making and even promoting social development.
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spelling pubmed-95189122022-09-29 Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications Li, Qi Wang, Xinbing Fu, Luoyi Wang, Jianghao Yao, Ling Gan, Xiaoying Zhou, Chenghu PLoS One Research Article The rapid development of modern science nowadays makes it rather challenging to pick out valuable ideas from massive scientific literature. Existing widely-adopted citation-based metrics are not adequate for measuring how well the idea presented by a single publication is developed and whether it is worth following. Here, inspired by traditional X-ray imaging, which returns internal structure imaging of real objects along with corresponding structure analysis, we propose Scientific X-ray, a framework that quantifies the development degree and development potential for any scientific idea through an assembly of ‘X-ray’ scanning, visualization and parsing operated on the citation network associated with a target publication. We pick all 71,431 scientific articles of citation counts over 1,000 as high-impact target publications among totally 204,664,199 publications that cover 16 disciplines spanning from 1800 to 2021. Our proposed Scientific X-ray reproduces how an idea evolves from the very original target publication all the way to the up to date status via an extracted ‘idea tree’ that attempts to preserve the most representative idea flow structure underneath each citation network. Interestingly, we observe that while the citation counts of publications may increase unlimitedly, the maximum valid idea inheritance of those target publications, i.e., the valid depth of the idea tree, cannot exceed a limit of six hops, and the idea evolution structure of any arbitrary publication unexceptionally falls into six fixed patterns. Combined with a development potential index that we further design based on the extracted idea tree, Scientific X-ray can vividly tell how further a given idea presented by a given publication can still go from any well-established starting point. Scientific X-ray successfully identifies 40 out of 49 topics of Nobel prize as high-potential topics by their prize-winning papers in an average of nine years before the prizes are released. Various trials on articles of diverse topics also confirm the power of Scientific X-ray in digging out influential/promising ideas. Scientific X-ray is user-friendly to researchers with any level of expertise, thus providing important basis for grasping research trends, helping scientific policy-making and even promoting social development. Public Library of Science 2022-09-28 /pmc/articles/PMC9518912/ /pubmed/36170296 http://dx.doi.org/10.1371/journal.pone.0275192 Text en © 2022 Li et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Li, Qi
Wang, Xinbing
Fu, Luoyi
Wang, Jianghao
Yao, Ling
Gan, Xiaoying
Zhou, Chenghu
Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title_full Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title_fullStr Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title_full_unstemmed Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title_short Scientific X-ray: Scanning and quantifying the idea evolution of scientific publications
title_sort scientific x-ray: scanning and quantifying the idea evolution of scientific publications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518912/
https://www.ncbi.nlm.nih.gov/pubmed/36170296
http://dx.doi.org/10.1371/journal.pone.0275192
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